There are 1 repository under cityscapes topic.
The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes
Add bisenetv2. My implementation of BiSeNet
Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)
PytorchAutoDrive: Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, RESA, LSTR, LaneATT, BĂ©zierLaneNet...) based on PyTorch with fast training, visualization, benchmarking & deployment help
SOTA Semantic Segmentation Models in PyTorch
Support PointRend, Fast_SCNN, HRNet, Deeplabv3_plus(xception, resnet, mobilenet), ContextNet, FPENet, DABNet, EdaNet, ENet, Espnetv2, RefineNet, UNet, DANet, HRNet, DFANet, HardNet, LedNet, OCNet, EncNet, DuNet, CGNet, CCNet, BiSeNet, PSPNet, ICNet, FCN, deeplab)
ICCV2021 (Oral) - Exploring Cross-Image Pixel Contrast for Semantic Segmentation
[CVPR 2021] Self-supervised depth estimation from short sequences
Understanding Convolution for Semantic Segmentation
This is Pytorch re-implementation of our CVPR 2020 paper "Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation" (https://arxiv.org/abs/1911.10194)
[ICLR 2020] "FasterSeg: Searching for Faster Real-time Semantic Segmentation" by Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang
Papers and Benchmarks about semantic segmentation, instance segmentation, panoptic segmentation and video segmentation
Pytorch code for semantic segmentation using ERFNet
[CVPR'22] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
TensorFlow-based implementation of "ICNet for Real-Time Semantic Segmentation on High-Resolution Images".
IJCAI2020 & IJCV2021 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo
[ECCV-2020]: Improving Semantic Segmentation via Decoupled Body and Edge Supervision
[ICCV19] AdaptIS: Adaptive Instance Selection Network, https://arxiv.org/abs/1909.07829
TensorFlow-based implementation of "Pyramid Scene Parsing Network".
Code of ICLR2023 paper "TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene Understanding" and ECCV2022 paper "Inverted Pyramid Multi-task Transformer for Dense Scene Understanding"
CGNet: A Light-weight Context Guided Network for Semantic Segmentation [IEEE Transactions on Image Processing 2020]
[NIVT Workshop @ ICCV 2023] SeMask: Semantically Masked Transformers for Semantic Segmentation
LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation
Unofficial tensorflow implementation of real-time scene image segmentation model "BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation"
Criss-Cross Attention (2d&3d) for Semantic Segmentation in pure Pytorch with a faster and more precise implementation.
Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (NeurIPS 2019 ML4AD)